We are seeking a Computational Protein Design Scientist to join our team working at the interface of generative AI and synthetic biology. You will play a key role amongst a team of scientists designing and engineering proteins for specific functions. This is an opportunity to help shape and grow an organization that advances artificial intelligence and applies it to longstanding scientific challenges. Using your blend of computational expertise and in-depth biochemical understanding of proteins, you will generate insights to improve protein functionality and operate at the interface between our machine learning and experimental platform units, working closely to seamlessly integrate AI generations and lab validation data.

At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.

Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.

We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.

• You are a computational protein designer. You have a proven track record of successfully leveraging novel computational tools and knowledge of biochemistry or structural biology to design proteins to functional requirements and applications in synthetic biology.
• You are a data scientist. You are a strong data scientist and you have experience owning data-driven projects to generate biological insights.
• You are a successful scientist. You have a PhD (or equivalent industry experience) in computational biology, bioinformatics, computer science, biochemistry, structural biology, physics, biophysics, bio/chem engineering, or a related field. Your research experience was in protein biochemistry using computational expertise.
• You collaborate with experimentalists. You have experience collaborating with experimental (i.e. wet lab) teams to achieve protein design objectives.
• You are an owner. You have a proven track record of delivering successful commercial and / or academic research projects, demonstrated through publications, patents, and/or commercially impactful outcomes, as well as other contributions to the scientific community.
• You are a connector. You love to connect people and enable them to perform at their highest levels. You have excellent communication and presentation skills with the ability to convey complex scientific concepts to both technical and non-technical audiences.
• You are a mission driven innovator. You are passionate about making a positive impact on the world, whether it's for patients, partners or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies.
• You thrive in a dynamic and ambiguous environment. You excel in a fast-paced setting where goals must be achieved efficiently and urgently. You have a keen eye for creating, then optimizing processes to improve speed and repeatability. You are an advocate for lab automation, both through hardware and software

• You have experience with generative AI. You have experience leveraging generative AI (or other machine learning models) in synthetic biology applications.
• You have experience engineering gene editing tools, such as nucleases and integrases.
• You have experience with homology-based and structural bioinformatics, and are able to answer scientific questions using very large databases.
• You have helped scale a young biotech before. You have worked in startups and helped the company grow.

• Leverage our proprietary generative AI models to design proteins for experimental validation:
  • Analyze protein design problems based on functional requirements, biochemistry, structural biology and sequence homology
  • Generate designs using our proprietary generative AI models and optimize designs for experimental validation
  • Coordinate with our lab-based protein engineers to plan and optimize the design process and validation strategy
• Leverage our proprietary data to improve our models:
  • Analyze and leverage our experimental results to improve the next round of designs and increase our success rate over validation rounds
  • Collaborate with machine learning scientists to fine-tune and prompt our models
• Collaboration and communication:
  • Be an effective interface between machine learning model development and experimental validation
  • Capture bioengineering learnings and feedback to our machine learning unit, and vice versa
  • Foster a collaborative and innovative environment, proactively finding opportunities to innovate and create clarity and alignment between different units
• Contribute to our computational tools:
  • Help improve the way we use, serve and integrate our AI models, by feeding back to the software engineers and foundational machine learning unit
  • Help improve our data management systems and workflows
• Scientific excellence and self development:
  • Work to the highest scientific standards (publication-grade work)
    Stay on top of relevant developments in synthetic biology
  • Continue building your understanding of generative AI as well as expanded areas of protein and cell biology
  • Participate in knowledge sharing, e.g. organize and present at our internal reading group.
  • Attend and present at conferences when relevant

We offer strongly competitive compensation and benefits packages, including:

• Private health insurance
• Pension/401(K) contributions
• Generous leave policies (including gender neutral parental leave)
• Hybrid working
• Travel opportunities and more

We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.

We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.

To apply, please fill in our application form.

We are looking for a highly skilled machine learning researcher with strong experience in generative modeling. You will join an interdisciplinary team of machine learners, software engineers, biologists and bioinformaticians, jointly working to change the way that we control biology and cure diseases. This is an opportunity to help shape and grow an organization that advances artificial intelligence and applies it to longstanding scientific challenges. In your role you will apply, refine and evaluate our proprietary generative models with the goal of designing new proteins that are functional in wet lab assays.

At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.

Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.

We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.

• You are a strong ML researcher. You have a proven track record of expertise in generative modeling. You have worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues.
• You are a skillful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write production-quality code. You have experience running training and inference on cloud hardware, distributing data and models across accelerators.
• You are a data engineer. You have experience building ML data pipelines for the training and evaluation of deep learning models. You are able to analyze the raw data, construct appropriate dataset splits and build pipelines that are performant and scalable.
• You have experience in optimizing generative models. You have optimized the sampling characteristics of generative models, such as diffusion and language models, and you have experience with finetuning them.
• You are an owner. You have a proven track record of delivering successful commercial or research outcomes. You drive projects forwards from conception to completion and see them through with great focus and leadership.
• You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are relentlessly curious about problems, however small or big they appear.
• You thrive in a dynamic environment. You excel in a fast-paced setting where goals must be achieved efficiently and urgently.

• You have experience in computational biology or protein design. You have worked on ML-driven projects in biology or conducted large scale bioinformatics analysis.
• You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.
• You have helped scale a young biotech before. You have worked in startups and helped the company grow.

• Apply our proprietary generative AI models to design proteins for experimental validation:
  • Closely collaborate with protein designers to generate designs using our proprietary generative AI models.
  • In collaboration with the biology team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab.
  • Leverage our proprietary data to improve our models:
  • Leverage our experimental results to finetune our models and improve the next round of designs.
  • Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.
  • Effectively translate between machine learning model development and experimental validation.
• Evaluate model capabilities:
  • Design informative benchmark tasks to track the performance of our models.
  • Closely collaborate with protein designers, bioinformaticians and biologists to ensure the biological relevance of our model evaluations.
• Self development:
  • Stay on top of the latest developments in ML.
  • Gain a strong working understanding of protein and cell biology.
  • Participate in knowledge sharing, e.g. organize and present at our internal reading group.
  • Attend and present at conferences when relevant.

We offer strongly competitive compensation and benefits packages, including:

• Private health insurance
• Pension/401(K) contributions
• Generous leave policies (including gender neutral parental leave)
• Hybrid working
• Travel opportunities and more

We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.

We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.

To apply, please fill in our application form.